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Deep learning

Deep learning is an AI function and subset of machine learning, used for processing large amounts of complex data.

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transformers
penpaperkeycode
penpaperkeycode commented Jun 2, 2022

Feature request

Is the addition of the 'OPTforSequenceClassification' class scheduled?
Is someone handling it?
When adding these functions, I wonder if it is possible to PR one by one, or if I have to PR all classes supported by other models.

Motivation

Added function of OPT class, which is being actively discussed recently

Your contribution

I personally use the forSequenceCla

kumpera
kumpera commented Jun 13, 2022

🚀 The feature, motivation and pitch

The current implementation of Zero Redundancy optimizer has its own implementation of object broadcasting.

We should replace it with c10d [broadcast_object_list](https://pytorch.org/docs/stable/distributed.html#torch.distributed.broadcast_object_lis

oncall: distributed module: bootcamp good first issue triaged

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  • Updated Apr 3, 2022
  • Python
VishDev12
VishDev12 commented Jun 4, 2022

What happened + What you expected to happen

When initializing a Ray Trainer, we provide a logdir argument, and the __init__ method of the Trainer stores it as a logdir class variable.

Then, when creating a Trainable with Trainer.to_tune_trainable(), it in-turn calls _create_tune_trainable(), which does not use self.logdir. So when tune_function is defined inside `_create_tu

bug good first issue P3 triage
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